Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM. - Yunyun Liang; Sanyang Liu; Shengli Zhang 002 (Comput. Math. Methods Medicine, 2015)

iR5hmcSC: Identifying RNA 5-hydroxymethylcytosine with multiple features based on stacking learning. - Shengli Zhang 002; Hongyan Shi (Comput. Biol. Chem., 2021)

R5hmCFDV: computational identification of RNA 5-hydroxymethylcytosine based on deep feature fusion and deep voting. - Hongyan Shi; Shengli Zhang 002; Xinjie Li (Briefings Bioinform., 2022)

An improved residual network using deep fusion for identifying RNA 5-methylcytosine sites. - Xinjie Li; Shengli Zhang 002; Hongyan Shi (Bioinform., 2022)

iPro-GAN: A novel model based on generative adversarial learning for identifying promoters and their strength. - Huijuan Qiao; Shengli Zhang 002; Tian Xue; Jinyue Wang; Bowei Wang (Comput. Methods Programs Biomed., 2022)

TNFIPs-Net: A deep learning model based on multi-feature fusion for prediction of TNF-α inducing epitopes. - Shengli Zhang 002; Yunyun Liang; Yujie Xu; Yuanyuan Jing (BIBM, 2023)

PreVFs-RG: A Deep Hybrid Model for Identifying Virulence Factors Based on Residual Block and Gated Recurrent Unit. - Shengli Zhang 002; Yuanyuan Jing (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

MMD-DTA: A Multi-Modal Deep Learning Framework for Drug-Target Binding Affinity and Binding Region Prediction. - Qi Zhang; Yuxiao Wei; Bo Liao; Liwei Liu 001; Shengli Zhang 002 (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)

An innovative peptide toxicity prediction model based on multi-scale convolutional neural network and residual connection. - Shengli Zhang 002; Jingyi Ren; Yunyun Liang (Bioinform., 2025)